Data Analyst (Temporary Assignment)

CACI International•Alexandria, VA

1d•$75,200 - $158,100•Remote

About The Position

The Deputy Assistant Secretary of Defense - Science and Technology (DASD-S&T) Futures and Foundations Office are seeking a proactive, detail-oriented data analyst to support day-to-day operations. DASD-S&T is responsible for policy and operation of defense laboratories and engineering centers. As a member of the DASD-S&T team, you will be on the cutting edge of where policy, science, and data analytics meet. This is a temporary position expected to run from August 14, 2026, through November 16, 2026, with the potential for extension based on organizational needs. This role allows you to work remotely; however, the client requires that you live in the Washington, D.C. Metro Area.

Requirements

Bachelor’s degree from an accredited college or university and a minimum of five (5) years of recent and relevant experience in the following: Data Engineering, Statistics or Data Analytics, Program Management
Knowledge of DoD data systems
Excellent written and oral communication skills
Active DoD TS/SCI clearance
Must live in the Washington, D.C. Metro Area.

Nice To Haves

Experience working in DoD RDTE enterprise.
Knowledge of SQL, Python, or R.
Knowledge or experience with Qlik, Databricks, Tableau, or other analytical platforms.
Experience utilizing DoD financial and contracting systems.
Understanding of the PPBE system and processes.
Knowledge of DoD FFRDC program management.

Responsibilities

Conduct a variety of data analyses on the performance of laboratory personnel systems, STEM (Science, Technology, Engineering, and Mathematics) outreach programs, technology transfer, infrastructure, and federally funded research and development centers (FFRDCs) to gauge the effectiveness and deficiencies and inform policy decisions based on findings.
Responding to client requests or proactively identifying data needs.
Determining the most suitable data systems for acquiring required information.
Processing acquired data using big data platforms, Microsoft Excel, PowerBI, DataBricks or Tableau for accuracy and relevance.
Conduct quality assurance procedures, including cleaning, labeling, and grouping data appropriately.
Develop visual representations of data to convey meaningful insights as per initial requirements.
Utilize existing data and databases to fulfill requests, reducing reliance on field calls.
Offer suggestions for refining data collection methods, minimizing repetitive queries, and enhancing precision.